بررسی آزمایشگاهی انتقال آلودگی در محیط متخلخل با استفاده از مدل ترکیبی عصبی فازی تطبیقی و درون یاب تابع پایه شعاعی

در این مطالعه، مدل جدیدی با استفاده از تلفیق روش سیستم عصبی فازی تطبیقی به عنوان یک روش جعبه سیاه برای پیش بینی زمانی و روش عددی بدون شبکه به عنوان یک مدل پایه فیزیکی برای پیش بینی مکانی غلظت آلاینده در محیط های متخلخل توسعه داده شد. برای این منظور یک مدل آزمایشگاهی دو بعدی ساخته شد و اسید نارنجی 7 (ao7) به عنوان آلاینده انتخاب گردید. آلاینده به مخزن بصورت غیریکنواخت وارد و در 10 نقطه مقدار آلاینده در زمانهای مختلف و با فواصل 3 دقیقه اندازه گیری شد. به منظور کاهش نویز در داده های اندازه گیری از روش آستانه موجک برای رفع نویز داده های مشاهداتی استفاده گردید. نتایج نشان داد که روش آستانه موجک توانایی مدل عصبی فازی تطبیقی را می تواند تا 5 درصد افزایش دهد. همپنین نتایج نشان داد که مدل ترکیبی سیستم عصبی فازی تطبیقی و روش بدون شبکه از توانایی مناسبی برای شبیه سازی انتقال آلودگی برخوردار است.

Experimental Study of Contaminant Transport in Porous Media Using ANFIS-RBF Hybrid Model

Some uncertainties in the field parameters such as dispersion and hydraulic conductivity, unknown boundary conditions and the noise of the measured data are among the main limiting factors in the groundwater flow and contaminant transport modeling. Thus, simulation of contaminant transport can be an important task in hydroenvironmental researchs and consequently, it is necessary to develop the robust models which can determine the temporal and spatial forecast of contaminant. For temporal modeling contaminant concentration, several numerical methods, such as finite volume method, finite difference method, boundary element method and finite element method have been used for computional solution of governing advectiondispersion partial differential equation. In this study, a new hybrid model based on adaptive neurofuzzy inference system (ANFIS) as an blackbox model and radial basis function (RBF) as a meshless method was developed. In fact, the proposed method employed the advantageous of both arthificial intelligence and meshless techniqus for modeling contaminant transport in porous media. In this research, an experimental was done for examining the efficiency of the proposed method. In this way, an acrylic sand tank was made with ten piezometers, one inlet with three adjustors. In order to supply contaminant a submersible pump was used. Also, constant water level was maintained using adjustor valves at both end of the tank. The thickness of acrylic sand tank 10 mm and dimensions 2.00 times;1.30 times;0.20 m3 were chosen. The sand sample porosity was measured 0.3. The grid size and time interval were considered 0.1 times;0.1 m times;m and 3minute, respectively. The constanthead test was employed to meaure the hydraulic conductivity of soil as a standard laboratory test. An UV Spectrophotometer (DR5000, HACH Company, USA) was used for measurement of the AO7 concentration. The maximum wavelength was measured 485 nm for AO7 concentration. Also, an electrical conductivity meter (EC600, A FLIR Company, USA) was used for measurement of the resistivity and electrical conductivity of AO7. In this study, time series of AO7 concentration observed at different piezometers of sand tank were firstly denoised by the waveletbased data denoising approach. Then, the effect of noisy and denoised data on the performance of ANFIS model was compared. For this end, time series of AO7 concentration observed in 10 different piezometers were trained and verified via ANFIS model to predict the AO7 concentration at one month ahead. Then, considering the predicted AO7 concentration of piezometers as interior conditions, the multiquadric radial basis function as a meshless method which solves partial differential equation of contaminant transport modeling in porous media, was employed to estimate AO7 concentration values at any point within the study area (in the experiment, sand tank) where there is not any piezometer. In this stage, optimal values of dispersion coefficient in advectiondispersion partial differential equation and shape coefficient of MQRBF were determined using cross validation approche. The cross validation method was finally applied to verify the performance of the proposed ANFISRBF model for two piezometers which were not considered in the calibration stage.In temporal contaminanat transport modeling, denoised data enhanced the performance of ANFIS methods up to 5 percent in the experimental study. Results showed that the efficiency of ANFISRBF model is a reliable thechnique for contaminant transport modeling in porous media.